Unsharp masking is a well-known image processing technique used to enhance high-frequency components (i.e., edges) of an image while suppressing some low amplitude noise. Typically, a low-pass filter is applied to the image to create a blurred version of the image. The low-pass filtered image is then compared to the original image to determine a difference between the low-pass filtered image and the original image. For each pixel of the original image, if the difference between the low-pass filtered image and the original image is above a threshold value that suppresses the low amplitude noise, then the difference is enhanced and combined with the low-pass filtered image to enhance the high frequency information in the image.
Conventional unsharp masking techniques apply the same filter kernel to the entire image. In many-cases, the noise varies spatially across the image such that the difference associated with the noisy pixels is above the threshold value implemented in the filter. In such cases, the noise may be enhanced thereby reducing the quality of the processed image. Thus, there is a need for addressing this issue and/or other issues associated with the prior art.